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Add 2024 End Child Poverty estimates
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Fixes #575
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zarino committed Sep 6, 2024
1 parent 558fe46 commit 9a3a168
Showing 1 changed file with 9 additions and 5 deletions.
14 changes: 9 additions & 5 deletions hub/management/commands/import_child_poverty_data.py
Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,8 @@
class Command(BaseImportFromDataFrameCommand):
help = "Import data about child poverty"

source_url = "https://endchildpoverty.org.uk/child-poverty/"
data_url = "https://endchildpoverty.org.uk/wp-content/uploads/2022/07/Child-Poverty-AHC-estimates-2015-2021-FINAL.xlsx"
source_url = "https://endchildpoverty.org.uk/child-poverty-2024/"
data_url = "https://aaf1a18515da0e792f78-c27fdabe952dfc357fe25ebf5c8897ee.ssl.cf5.rackcdn.com/2010/Chid+poverty+AHC+2015-2023_Local+Authorities+and+Constituencies.xlsx?v=1716657555000"

cast_field = FloatField
uses_gss = True
Expand All @@ -22,7 +22,7 @@ class Command(BaseImportFromDataFrameCommand):
"defaults": {
"label": "Estimated child poverty",
"description": "Percentage of children living in households with a net income (after housing costs) below 60% of the national median.",
"release_date": "March 2022",
"release_date": "June 2024",
"data_type": "percent",
"category": "place",
"source_label": "Data from End Child Poverty, based on data from DWP/HMRC.",
Expand All @@ -36,7 +36,7 @@ class Command(BaseImportFromDataFrameCommand):
"unit_type": "percentage",
"unit_distribution": "people_in_area",
},
"col": "Percentage 2020/21",
"col": "Percentage 2022-23",
}
}

Expand All @@ -60,14 +60,18 @@ def get_dataframe(self):
"Number 2018/19",
"Number 2019/20",
"Number 2020/21",
"Number 2021/22",
"Number 2022-23",
"Percentage 2014/15",
"Percentage 2015/16",
"Percentage 2016/17",
"Percentage 2017/18",
"Percentage 2018/19",
"Percentage 2019/20",
"Percentage 2020/21",
"Percentage point change (2015-21)",
"Percentage 2021/22",
"Percentage 2022-23",
"Percentage point change (2015-22)",
]
percentage_columns = [col for col in df.columns if "Percentage" in col]
for col in percentage_columns:
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